The Data Stack is the structured foundation of Soma’s metric ecosystem.
It visualizes the core outputs Soma tracks across every task, providing a comprehensive analysis of an athlete’s cognitive and physiological performance.
Soma’s Data Stack Includes Two Primary Categories:
Cognitive Metrics
Reaction Time
Reaction Time measures the time (in milliseconds) it takes to respond to a stimulus.
Speed
Speed (1000/RT) transforms reaction time in a way that makes peaks and fluctuations more visible—stretching out differences in faster responses so that big neural events, which might be subtle in reaction time, appear as clear peaks in speed. This makes it more useful for detecting high-performance changes, neural processing shifts, and cognitive adaptation over time.
Variation (Coefficient of Variation)
Variation measures the relative variability in an athlete’s performance by comparing how widely responses fluctuate around the mean.
Rate Correct Score (RCS)
RCS measures how many correct responses an athlete delivers per second — capturing the balance between speed and accuracy in a single metric.
Accuracy
Accuracy measures the percentage of correct responses an athlete makes in a task. It reflects precision and consistency in performance.
Physiological Metrics
These metrics monitor the body’s autonomic responses, providing insights into stress levels and recovery capacity:
BPM (Beats Per Minute): Tracks heart rate, offering a basic measure of cardiovascular activity during cognitive tasks. Elevated BPM may indicate increased mental effort or stress.
rMSSD (Root Mean Square of Successive Differences): Assesses short-term heart rate variability, reflecting parasympathetic nervous system activity and the body’s ability to manage stress and recover. Higher rMSSD values suggest effective stress management.
SDNN (Standard Deviation of Normal-to-Normal Intervals): Measures overall heart rate variability, encompassing both sympathetic and parasympathetic influences. Higher SDNN values indicate better cardiovascular health and autonomic flexibility.
Minute on Minute (MoM)
Most systems stop at averages. Soma doesn’t.
We track both mean and minute-on-minute (MoM) performance — to reveal how fatigue evolves in real time.
Because fatigue doesn’t show up in the average.
It leaks. Slowly. Then suddenly.
MoM tells you:
When performance starts to slip
How it fails
And what metric collapsed first
This is where Soma separates from the field.